Metadata-Version: 2.1
Name: qibullet
Version: 1.4.3
Summary: Bullet-based simulation for SoftBank Robotics' robots
Home-page: https://github.com/softbankrobotics-research/qibullet
Author: Maxime Busy, Maxime Caniot
Author-email: 
License: UNKNOWN
Description: # qiBullet [![unit-tests](https://github.com/softbankrobotics-research/qibullet/workflows/unit-tests/badge.svg?branch=master)](https://github.com/softbankrobotics-research/qibullet/actions?query=workflow%3Aunit-tests) [![codecov](https://codecov.io/gh/softbankrobotics-research/qibullet/branch/master/graph/badge.svg)](https://codecov.io/gh/softbankrobotics-research/qibullet) [![pypi](https://img.shields.io/pypi/v/qibullet.svg)](https://pypi.org/project/qibullet/) [![Downloads](https://pepy.tech/badge/qibullet)](https://pepy.tech/project/qibullet) [![Gitter chat](https://badges.gitter.im/qibullet.png)](https://gitter.im/qibullet "Gitter chat")
        
        __Bullet-based__ python simulation for __SoftBank Robotics'__ robots.
        
        
        
        ## Installation
        
        The following modules are required:
        * __numpy__
        * __pybullet__
        
        The qiBullet module can be installed via pip, for python 2.7 and python 3:
        ```bash
        pip install --user qibullet
        ```
        
        Additional resources (robot meshes and URDFs) are required in order to be able to spawn a Pepper, NAO or Romeo robot in the simulation. These extra resources will be installed in your home folder:
        * `/home/username/.qibullet` on Linux and macOS
        * `C:\Users\username\.qibullet` on Windows
        
        The installation of the additional resources will automatically be triggered if you try to spawn a Pepper, NAO or Romeo for the first time. If qiBullet finds the additional resources in your local folder, the installation won't be triggered. The robot meshes are under a specific [license](https://github.com/softbankrobotics-research/qibullet/tree/master/qibullet/robot_data/LICENSE), you will need to agree to that license in order to install them. More details on the installation process can be found on the [wiki](https://github.com/softbankrobotics-research/qibullet/wiki).
        
        ## Usage
        A robot can be spawned via the SimulationManager class:
        ```python
        from qibullet import SimulationManager
        
        if __name__ == "__main__":
            simulation_manager = SimulationManager()
        
            # Launch a simulation instances, with using a graphical interface.
            # Please note that only one graphical interface can be launched at a time
            client_id = simulation_manager.launchSimulation(gui=True)
        
            # Selection of the robot type to spawn (True : Pepper, False : NAO)
            pepper_robot = True
        
            if pepper_robot:
              # Spawning a virtual Pepper robot, at the origin of the WORLD frame, and a
              # ground plane
              pepper = simulation_manager.spawnPepper(
                  client_id,
                  translation=[0, 0, 0],
                  quaternion=[0, 0, 0, 1],
                  spawn_ground_plane=True)
            else:
              # Or a NAO robot, at a default position
              nao = simulation_manager.spawnNao(
                  client_id,
                  spawn_ground_plane=True)
        ```
        
        Or using loadRobot from the PepperVirtual class if you already have a simulated environment:
        ```python
            pepper = PepperVirtual()
        
            pepper.loadRobot(
              translation=[0, 0, 0],
              quaternion=[0, 0, 0, 1],
              physicsClientId=client_id)
        ```
        
        More snippets can be found in the [examples folder](https://github.com/softbankrobotics-research/qibullet/tree/master/examples), or on the [wiki](https://github.com/softbankrobotics-research/qibullet/wiki)
        
        > :warning: The camera subscription system of qiBullet 1.4.0 (and lesser) is __deprecated__, use the [new system](https://github.com/softbankrobotics-research/qibullet/wiki/Tutorials:-Virtual-Robot#cameras)
        
        ## Documentation
        The qiBullet __API documentation__ can be found [here](https://softbankrobotics-research.github.io/qibullet/api/). The documentation can be generated via the following command (the __doxygen__ package has to be installed beforehand, and the docs folder has to exist):
        ```bash
        cd docs
        doxygen
        ```
        
        The repository also contains a [wiki](https://github.com/softbankrobotics-research/qibullet/wiki), providing some tutorials.
        
        ## Citations
        Please cite qiBullet if you use this repository in your publications:
        ```
        @article{busy2019qibullet,
          title={qiBullet, a Bullet-based simulator for the Pepper and NAO robots},
          author={Busy, Maxime and Caniot, Maxime},
          journal={arXiv preprint arXiv:1909.00779},
          year={2019}
        }
        ```
        
        ## Troubleshooting
        
        ### OpenGL driver
        If you encounter the message:
        > Workaround for some crash in the Intel OpenGL driver on Linux/Ubuntu
        
        Your computer is using the Intel OpenGL driver. Go to __Software & Updates__, __Additional Drivers__, and select a driver corresponding to your GPU.
        
        ## License
        Licensed under the [Apache-2.0 License](LICENSE)
        
Keywords: physics simulation,robotics,naoqi,softbank,pepper,nao,romeo,robot
Platform: UNKNOWN
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Developers
Classifier: Operating System :: POSIX :: Linux
Classifier: Operating System :: MacOS
Classifier: Operating System :: Microsoft
Classifier: Topic :: Games/Entertainment :: Simulation
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Framework :: Robot Framework :: Tool
Description-Content-Type: text/markdown
